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Data + Relationships = Information

puzzledAll the pieces of data that we have mean very little on their own, but when we add relationships to that data it becomes useful “data” or what we call information. Let’s consider these trivial pieces of data below as an example:

200, Borg, 99019901, Joseph, Merchant’s Street, Valletta, ,

The relationships seem so obvious in this case that our minds start organising that data and making assumptions such as; the name is Joseph, Valletta is part of the address, 99019901 must be mobile number, the address must be linked to the person and so on until we get the relationships sorted to form a name, surname, address and telephone number that are presumably linked together. So here we applied relationships and logic that we’re familiar with to a line of data to change it into some piece of information that is more usable for us. Something that is more familiar.

The same applies to more complex pieces of data. We need to apply relationships in the form of logical structure and links to convert it into useful information that we can make use of. Consider the different bits of data that we all have within our organisations. Let consider a more complex example:

  1. Receipts of items bought.
  2. delivery notes of items sold.

These 2 sets of information have some use on their own. We can calculate costs, sales and profit. However if we start adding relationships to those 2 sets of “data” we can extract information that might be more useful to us to turn a better profit:

  • Profitability of each item
  • Seasonality of each item
  • Shelf life of each item
  • Shelving cost of each item
  • Recommended Stock Levels for each item
  • Current Stock Levels of all items
  • Most profitable products
  • Least profitable products
  • Products that sell in a regular pattern
  • Products that sell in an irregular pattern
  • Brand Comparison for the same type of product
  • Returns per item
  • And more…

So as you can see just by linking items from purchase receipts to sales receipts we can start extracting management information that can guide our day to day operations towards better efficiency and more profit. Such processing is the realm of IT.

Our brains excel at applying assumptions to organise pieces of data into seemingly useful information and most of the time we’re confident that our assumptions are correct, but it is rarely so. In reality it is only through IT that we can process volumes of data to extract useful information reliably and unassumingly. Information that can make all the difference in our organisation. Let’s point out that the data in the first example was meant to be read as follows: “Deliver 200 items of product “Borg”, (product ID:99019901) to Address: “Joseph, Merchant’s Street, Valletta, no postcode”. Most of us got our assumptions wrong.

Are you making the best use of your data or are you losing out on the information you could have? Are you the assuming type or are you the logical type?


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